Trust by Design: Enabling Responsible Precision Health Through Blockchain-Powered Digital Twins and Trusted AI: Conv2X 2025 Conference Executive Session
DOI:
https://doi.org/10.30953/bhty.v8.453Keywords:
AI, artificial intelligence, blockchain, digital twins, interoperability, precision health, personalized medicine, privacy, standards, trusted cybersecurityAbstract
The Executive Session, Trust by Design: Enabling Responsible Precision Health through Blockchain-Powered Digital Twins and Trusted AI, convened during ConV2X 2025 to explore how the convergence of blockchain, artificial intelligence, genomics, 6G wireless technology, and other advanced technologies can be leveraged to power precision health digital twins. The dialogue focused on governance, interoperability, cybersecurity, and the impact of blockchain and trusted AI-powered digital twins on advancing precision healthcare and personalized medicine. Use cases—for genomics, radiology, theranostics, and end-of-life care—illustrated both opportunities and barriers. Throughout the discussion, speakers emphasized the centrality of trust, patient sovereignty, and resilient infrastructures for the next generation of healthcare.
Downloads
References
Singh B, Malviya R, Kaunert C, editors. Metaverse and digital twins: Blockchain and healthcare technology. Walter de Gruyter GmbH & Co KG; 2025.
El-Din HE, Amged S. Smart and secure healthcare with digital twins: A deep dive into blockchain, federated learning, and future innovations. Algorithms. 2025;18(7):401. doi:10.3390/a18070401
Etindele Sosso FA, Cousineau M, Paré G. Advancing health care with digital twins: Meta-review of applications and implementation challenges. Journal of Medical Internet Research. 2025;27:e69544. doi:10.2196/69544
Oulefki A, Amira A, Foufou S. Digital twins and AI transforming healthcare systems through innovation and data-driven decision making. Health and Technology. 2025;:1–23. doi:10.1007/s12553-025-00615-2
Wu B, Huang J, Duan Q. Real-time intelligent healthcare enabled by federated digital twins with AI optimization. IEEE Network. 2025. Epub ahead of print. doi:10.1109/MNET.2025.3021111
Roopa MS, Venugopal KR. Digital twins for cyber-physical healthcare systems: Architecture, requirements, systematic analysis and future prospects. IEEE Access. 2025. Epub ahead of print. doi:10.1109/ACCESS.2025.2983456
Pellegrino G, Gervasi M, Angelelli M, Corallo A. A conceptual framework for digital twin in healthcare: Evidence from a systematic meta-review. Information Systems Frontiers. 2025;27(1):7–32. doi:10.1007/s10796-024-10512-x
de Oliveira El-Warrak L, Miceli de Farias C. Could digital twins be the next revolution in healthcare? European Journal of Public Health. 2025;35(1):19–25. doi:10.1093/eurpub/ckz276
Jain K, Agarwal A, Agrawal S, Aggarwal A. Digital twins in modern healthcare: A comprehensive review of architectures, applications, and challenges. Wiley Interdisciplinary Reviews: Computational Statistics. 2025;17(3):e70041. doi:10.1002/wics.70041
Repetto M, Colapinto C, Jayaraman R, Appio F, La Torre D. Blockchain-enabled predictive digital twin approach for healthcare: Enhancing accuracy and performance with federated learning. International Journal of Production Economics. 2025;109768. doi:10.1016/j.ijpe.2025.109768
Vallée A. Digital twins for personalized medicine require epidemiological data and mathematical modeling. Journal of Medical Internet Research. 2025;27:e72411. doi:10.2196/72411
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Ingrid Vasiliu-Feltes, Dr. Christina Yan Zhang, Prof. Dr. Stephen Dennis, Prof. Dr. Elliot Siegel, Mr. Daniel Uribe

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors retain copyright of their work, with first publication rights granted to Blockchain in Healthcare Today (BHTY). Read the full Copyright Statement.














